Instructions to use junaidali/bert_tokenizer_updated_multilingual_words with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use junaidali/bert_tokenizer_updated_multilingual_words with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="junaidali/bert_tokenizer_updated_multilingual_words")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("junaidali/bert_tokenizer_updated_multilingual_words") model = AutoModelForTokenClassification.from_pretrained("junaidali/bert_tokenizer_updated_multilingual_words", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a7b40572ca871bb40660f6d43dc954e47963f6657b5a1d321c673fc61ffd754
- Size of remote file:
- 27.8 MB
- SHA256:
- 32ff580c6f0d60c1a203015a04a44a35514c31202a6431407da3e7f0bcc55cee
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